Roozbeh Kianfar

Design and Experimental Validation of a Cooperative Driving System in the Grand Cooperative Driving Challenge

In this paper, we present the Cooperative Adaptive Cruise Control (CACC) architecture, which was proposed and implemented by the team from Chalmers University of Technology, Göteborg, Sweden, that joined the Grand Cooperative Driving Challenge (GCDC) in 2011. The proposed CACC architecture consists of the following three main components, which are described in detail: 1) communication; 2) sensor fusion; and 3) control. Both simulation and experimental results are provided, demonstrating that the proposed CACC system can drive within a vehicle platoon while minimizing the inter-vehicle spacing within the allowed range of safety distances, tracking a desired speed profile, and attenuating acceleration shockwaves.

A receding horizon approach to string stable cooperative adaptive cruise control

A time domain approach to a “string stable”, i.e., capable of attenuating acceleration shockwaves, cooperative adaptive cruise control is proposed in this paper. A receding horizon scheme is adopted to design a controller which attenuates acceleration shockwaves generated by the preceding vehicle while avoiding rear-end collisions. The classical definition of string stability in frequency domain is revised in the time domain and a new criterion for predecessor-follower string stability based on the acceleration signals is defined and used. Simulation and experimental results are presented to show the effectiveness of the proposed method.

Safety Verification of Automated Driving Systems

In this paper, a set based approach is presented for safety verification and performance analysis of automated driving systems. As an example, reachability analysis technique is used to study the minimum required safe inter-vehicle distance for two given adaptive cruise controllers, a state feedback and a state feedback/feedforward controller designed based on mixed d H2/3 control. Not surprisingly, the results indicate that a shorter inter-vehicle distance can be achieved when a feedforward term used in the controller. In addition, we show how backward reachability analysis and invariant set theory can be used to find the Maximal Admissible Safe Set. This is defined as the set of position error, relative speeds and acceleration, which a given controller is guaranteed to control to the desired speed and inter-vehicle distance, while fulfilling vehicle physical constraints and avoiding rear-end collisions with the preceding vehicle. The calculation of the Maximal Admissible Safe Set is demonstrated for the two aforementioned controllers. Furthermore, the presented verification method is extended to account for the case of vehicle model with polytopic uncertainties and delay. The results on the reachability analysis are verified experimentally using an emergency braking scenario.

Combined Longitudinal and Lateral Control Design for String Stable Vehicle Platooning within a Designated Lane

We propose a combined longitudinal and lateral control approach for vehicle platooning within a designated lane. We combine linear frequency and time domain methods, to design longitudinal control that ensures string stability while enforcing safety, comfort and actuator limitations. In addition, we design lateral control that accounts for speed variations induced by the longitudinal control as well as safety, comfort and actuator limitations using convex optimization methods.

Reachability analysis of cooperative adaptive cruise controller

In this paper, a set based approach to safety analysis of Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) is presented. Reachability analysis techniques are used to compare the minimum safe intervehicle distances which can be achieved with ACC and CACC controllers. Not surprisingly, the results indicate that a shorter inter-vehicle distance can be achieved with a CACC controller. The presented method can also be used to design the required inter-vehicle distance for a given controller. Furthermore, we show how backward reachability analysis and invariant set theory can be used to find the Maximal Asymptotic Safe Set. This is defined as a set of position error, relative speeds and acceleration, which a given controller is guaranteed to control to the desired speed and inter-vehicle distance, while fulfilling vehicle physical constraints and avoiding rear-end collisions with the preceding vehicle. The calculation of the Maximal Asymptotic Safe Set is demonstrated for ACC and CACC controller designed based on mixed H2/∞ state feedback. Finally, the calculation of the Maximal Asymptotic Safe Set is extended to the case of vehicle model uncertainties.

A Distributed Model Predictive Control Approach to Active Steering Control of String Stable Cooperative Vehicle Platoon

A distributed receding horizon approach is adopted for active steering control of a cooperative vehicle platoon in the lateral direction. String stability is enforced by translating the classical definition of string stability from frequency domain into time domain constraint. Each vehicle locally computes its own control action and broadcasts its intention to its follower. Any deviation from the intention of each vehicle from the predicted states is penalized and constrained in the optimization problem which is solved locally by the vehicles. The string stability condition is robust against uncertainty in the intent trajectory. The effectiveness of proposed approach is verified by simulation in a double lane change scenario.

A Control Matching-based Predictive Approach to String Stable Vehicle Platooning

A predictive control strategy for vehicle platoons is presented in this paper, accommodating both string stability and constraints (e.g., physical and safety) satisfaction. In the proposed design procedure, the two objectives are achieved by matching a Model Predictive Controller (MPC), enforcing constraints satisfaction, with a linear controller designed to guarantee string stability. The proposed approach neatly combines the straightforward design of a string stable controller in the frequency domain, where a considerable number of approaches have been proposed in literature, with the capability of a MPC-based controller of enforcing state and input constraints. A controller obtained with the proposed design procedure is validated in simulations, showing how string stability and constraints satisfaction can be simultaneously achieved with a single controller. The operating region that the MPC controller is string stable is characterized by the interior of feasible set of the MPC controller.

Automated controller design using linear quantitative feedback theory for nonlinear systems

A method to design simple linear controllers for mildly nonlinear systems is presented. In order to design the desired controller we approximate the behavior of the nonlinear system with a set of linear systems which are derived through linearizations. Classical local linearization is carried out around stationary points but in order to have a better approximation of the nonlinear system selected non-stationary points are taken into account as well. This set of linear models are considered as an uncertainty description for a nominal plant. Qunatitative Feedback theory (QFT) may be used to guarantee specification to be fulfilled for all linear models in such an uncertainty set. Traditionally QFT design is carried out in a Nichols diagram by loop shaping of the nominal linear plant. This task highly depends on the experience of the designer and is difficult for unstable systems. In order to facilitate this task an optimization algorithm based on Genetic algorithm is used to automatically synthesize a fixed structure controller. For illustration and evaluation the method is succesfully applied to a Wiener system and a nonlinear Bioreactor benchmark problem.

Safe autonomous lane changes in dense traffic

Lane change manoeuvres are complex driving manoeuvres to automate since the vehicle has to anticipate and adapt to intentions of several surrounding vehicles. Selecting a suitable gap to move/merge into the adjacent lane and performing the lane change can be challenging, especially in dense traffic. Existing gap selection methods tend to be either cautious or opportunistic, both of which directly affect the overall availability and safety of the autonomous feature. In this paper we present a method which enables the autonomous vehicles to increase the availability of lane change manoeuvres by reducing the required margins to ensure a safe manoeuvre. The required safety margins are first calculated by making use of the steering and braking capability of the vehicle. It is then shown that this method can be used to perform autonomous lane changes in dense traffic situations with small inter-vehicle gaps. The proposed solution is evaluated by using Model Predictive Control (MPC) to plan and execute the complete motion trajectory.

Towards Integrated Design of Plant/Controller With Application in Mechatronics Systems

In this paper, a method is proposed for integrated design of mechatronics systems. The integrated design problem is formulated as a semi-definite programming optimization problem. However, this is an infinite dimensional convex optimization problem, which is hard to solve. In this paper, it is shown that a vertex enumeration method can be used to transform the infinite dimensional optimization problem into a finite dimensional problem, which under the assumptions that the state space matrices are affine function of structural variables and that the structural variables belong to a polytope, can be solved efficiently. To show the effectiveness of the method, the method is applied to a mechatronics system.